Towards the Automation of Infrared Thermography Inspections for Industrial Maintenance Applications.

The maintenance of industrial equipment extends its useful life, improves its efficiency, reduces the number of failures, and increases the safety of its use. This study proposes a methodology to develop a predictive maintenance tool based on infrared thermographic measures capable of anticipating failures in industrial equipment. The thermal response of selected equipment in normal operation and in controlled induced anomalous operation was analyzed. The characterization of these situations enabled the development of a machine learning system capable of predicting malfunctions. Different options within the available conventional machine learning techniques were analyzed, assessed, and finally selected for electronic equipment maintenance activities. This study provides advances towards the robust application of machine learning combined with infrared thermography and augmented reality for maintenance applications of industrial equipment. The predictive maintenance system finally selected enables automatic quick hand-held thermal inspections using 3D object detection and a pose estimation algorithm, making predictions with an accuracy of 94% at an inference time of 0.006 s.

High-performance vector bending and orientation distinguishing curvature sensor based on asymmetric coupled multi-core fibre.

Fibre optic technology is rapidly evolving, driven mainly by telecommunication and sensing applications. Excellent reliability of the manufacturing processes and low cost have drawn ever increasing attention to fibre-based sensors, e.g. for studying mechanical response/limitations of aerospace composite structures. Here, a vector bending and orientation distinguishing curvature sensor, based on asymmetric coupled multi-core fibre, is proposed and experimentally demonstrated. By optimising the mode coupling effect of a seven core multi-core fibre, we have achieved a sensitivity of - 1.4 nm/° as a vector bending sensor and - 17.5 nm/m-1 as a curvature sensor. These are the highest sensitivities reported so far, to the best of our knowledge. In addition, our sensor offers several advantages such as repeatability of fabrication, wide operating range and small size and weight which benefit its sensing applications.

Sliding Mode Control with Dynamical Correction for Time-Delay Piezoelectric Actuator Systems.

In piezoelectric actuators (PEAs), which suffer from inherent nonlinearities, sliding mode control (SMC) has proven to be a successful control strategy. Nonetheless, in micropositioning systems with time delay, integral proportional control (PI), and SMC, feedback control schemes have a tendency to overcompensate and, consequently, high controller gains must be rejected. This may produce a slow and inaccurate response. This paper presents a novel control strategy that deals with time-delay micropositioning systems aimed at achieving precise positioning by combining an open-loop control with a modified SMC scheme. The proposed SMC with dynamical correction (SMC-WDC) uses the dynamical system model to adapt the SMC inputs and avoid undesirable control response caused by delays. In order to develop the SMC-WDC scheme, an exhaustive analysis on the micropositioning system was first performed. Then, a mixed control strategy, combining inverse open-loop control and SMC-WDC, was developed. The performance of the presented control scheme was analyzed and compared experimentally with other control strategies (i.e., PI and SMC with saturation and hyperbolic functions) using different reference signals. It was found that the SMC-WDC strategy presents the best performance, that is, the fastest response and highest accuracy, especially against sudden changes of reference setpoints (frequencies >10 Hz). Additionally, if the setpoint reference frequencies are higher than 10 Hz, high integral gains are counterproductive (since the control response increases the delay), although if frequencies are below 1 Hz the integral control delay does not affect the system's accuracy. The SMC-WDC proved to be an effective strategy for micropositioning systems, dealing with time delay and other uncertainties to achieve the setpoint command fast and precisely without chattering.

Accurate strain sensing based on super-mode interference in strongly coupled multi-core optical fibres.

We report on the use of a multi-core fibre (MCF) comprising strongly-coupled cores for accurate strain sensing. Our MCF is designed to mode match a standard single mode optical fibre. This allows us to fabricate simple MCF interferometers whose interrogation is carried out with light sources, detectors and fibre components readily available from the optical communications tool box. Our MCF interferometers were used for sensing strain. The sensor calibration was carried out in a high-fidelity aerospace test laboratory. In addition, a packaged MCF interferometer was transferred into field trials to validate its performance under deployment conditions, specifically the sensors were installed in a historical iron bridge. Our results suggest that the MCF strain sensors here proposed are likely to reach the readiness level to compete with other mature sensor technologies, hence to find commercial application. An important advantage of our MCF interferometers is their capability to operate at very high temperatures.